def draw_conv_series(self, x, shape=None):
x = np.array(x)
for xx in x:
VisUtil.show_img(VisUtil.trans_img(xx, shape), "Original")
for i, (layer, ac) in enumerate(
zip(
self._layers,
self._get_acts(
np.array([xx.transpose(1, 2, 0)],
dtype=np.float32)))):
if len(ac.shape) == 4:
VisUtil.show_batch_img(
ac[0].transpose(2, 0, 1),
"Layer {} ({})".format(i + 1, layer.name))
else:
ac = ac[0]
length = sqrt(np.prod(ac.shape))
if length < 10:
continue
(height,
width) = xx.shape[1:] if shape is None else shape[1:]
sqrt_shape = sqrt(height * width)
oh, ow = int(length * height / sqrt_shape), int(
length * width / sqrt_shape)
VisUtil.show_img(ac[:oh * ow].reshape(oh, ow),
"Layer {} ({})".format(i + 1, layer.name))
def draw_conv_weights(self):
with self._sess.as_default():
for i, (name, weight) in enumerate(zip(self.layer_names, self._tf_weights)):
weight = weight.eval()
if len(weight.shape) != 4:
continue
for j, _w in enumerate(weight.transpose(2, 3, 0, 1)):
VisUtil.show_batch_img(_w, "{} {} filter {}".format(name, i + 1, j + 1))
def draw_conv_weights(self):
with self._sess.as_default():
for i, (name, weight) in enumerate(zip(self.layer_names, self._tf_weights)):
weight = weight.eval()
if len(weight.shape) != 4:
continue
for j, _w in enumerate(weight.transpose(2, 3, 0, 1)):
VisUtil.show_batch_img(_w, "{} {} filter {}".format(name, i + 1, j + 1))
def draw_conv_series(self, x, shape=None):
x = np.asarray(x)
for xx in x:
VisUtil.show_img(VisUtil.trans_img(xx, shape), "Original")
for i, (layer, ac) in enumerate(zip(
self._layers, self._get_acts(np.array([xx.transpose(1, 2, 0)], dtype=np.float32)))):
if len(ac.shape) == 4:
VisUtil.show_batch_img(ac[0].transpose(2, 0, 1), "Layer {} ({})".format(i + 1, layer.name))
else:
ac = ac[0]
length = sqrt(np.prod(ac.shape))
if length < 10:
continue
(height, width) = xx.shape[1:] if shape is None else shape[1:]
sqrt_shape = sqrt(height * width)
oh, ow = int(length * height / sqrt_shape), int(length * width / sqrt_shape)
VisUtil.show_img(ac[:oh * ow].reshape(oh, ow), "Layer {} ({})".format(i + 1, layer.name))
